{"id":"W4282946320","doi":"10.1039/d2cp00247g","title":"Improving the accuracy of the variational quantum eigensolver for molecular systems by the explicitly-correlated perturbative [2]<sub>R12</sub><b>-</b>correction","year":2022,"lang":"en","type":"article","venue":"Physical Chemistry Chemical Physics","topic":"Molecular spectroscopy and chirality","field":"Chemistry","cited_by":29,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canadian Institute for Advanced Research; Vector Institute; University of Toronto","funders":"RWTH Aachen University; Deutscher Akademischer Austauschdienst; Government of Ontario; Compute Canada; University of Toronto; U.S. Department of Energy","keywords":"Wave function; Gaussian; Atomic orbital; Computation; Basis (linear algebra); Basis set; Computer science; Context (archaeology); Quantum computer; Quantum; Statistical physics; Applied mathematics; Physics; Algorithm; Mathematics; Quantum mechanics; Electron; Density functional theory","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001550167,0.0007273618,0.0006431377,0.0005244194,0.0009937831,0.001193734,0.002044601,0.001134271,0.009352368],"category_scores_gemma":[0.006937725,0.0003209741,0.0004683524,0.0006880937,0.0008778249,0.001408726,0.00102138,0.001950037,0.002001386],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008284209,"about_ca_system_score_gemma":0.001482324,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00473803,"about_ca_topic_score_gemma":0.008959272,"domain_scores_codex":[0.9993781,0.000215549,0.00002907975,0.00004548242,0.0002705564,0.00006128191],"domain_scores_gemma":[0.997733,0.0009998804,0.00009923919,0.0007204423,0.0003769425,0.00007053339],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002031906,0.0002098292,0.002525927,0.0003693238,0.0001003892,0.0001719216,0.0002350064,0.4585323,0.02973602,0.3994141,0.006962833,0.1015392],"study_design_scores_gemma":[0.00001218035,0.00002855962,0.0002522163,0.0000303355,0.000007174936,0.00003625591,0.00002402433,0.9455653,0.006254479,0.04505862,0.002709016,0.00002189335],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.06745353,0.0003793664,0.8873101,0.001193871,0.0003911569,0.0001235056,0.0005261253,0.002264986,0.04035737],"genre_scores_gemma":[0.6693565,0.0004177182,0.3190816,0.0004678503,0.0001024143,0.000198803,0.000393404,0.001841401,0.008140342],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.009352368,"threshold_uncertainty_score":0.03128678,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007548396597480292,"score_gpt":0.2232203588528682,"score_spread":0.2156719622553879,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}